The sharpening of video images using software may be of interest in many different applications. Applications in which such techniques might be desirable include, for example, multimedia teleconferencing, video surveying and medical imaging. Software enhancement of images may be of particular interest whenever video streaming techniques are employed.
Consider a video teleconferencing system, in which a corresponding system is implemented in the personal computers of each participant. Each system includes a small camera, which may be mounted on the monitor of each computer. Furthermore, each system includes appropriate video conferencing application software, such as the Proshare Video Conferencing System available from Intel Corporation of Santa Clara, Calif. Hence, an image of each participant of a video conference may be recorded while he is watching his monitor. The images are transmitted from a local system to a remote system over a suitable data link, such as telephone lines or an Integrated Services Digital Network (ISDN) link. As a result, images of some or all participants may be displayed on each monitor during a video conference.
In video conferencing systems, it is desirable to reduce the overall costs of the required hardware. Therefore, the video cameras should be as simple as possible. Hence, it may not be desirable to employ an autofocus mechanism. However, it is also undesirable to have to focus manually during a conference.
In order to understand existing video processing technology, it should first be noted that video images are commonly made up of fundamental picture elements, which are often referred to as pixels. In a simple example, pixels might appear either black or white and should be small compared to the full size of the image. As further illustrated in FIG. 2a, a two-dimensional, rectangular black box 200 in a white surrounding may be chosen as an object to be displayed. Hence, according to FIG. 2b, a sharp image 210 of the box 200 might consist of a plurality of black pixels 220 forming a two-dimensional, rectangular box surrounded by a plurality of white pixels 225. On the other hand, as indicated in FIG. 2c, a blurred (non-sharp) image 230 might consist of further, undesired black pixels 240 outside of an area 250 corresponding to the sharp image of the box 200, and some white pixels 245 inside of the area 250.
A sharper image might be obtained from an initial image by applying rules such as the following: take a first white pixel within a blurred image; compare the numbers of black and white pixels in the immediate neighborhood of the white pixel; change the first white pixel into a black pixel if there is a majority of black pixels in its immediate neighborhood; leave the first white pixel as it is if there is the same number or a majority of white pixels in the immediate neighborhood of the first white pixel. Further rules for pixels which are initially black can be obtained while swapping black and white in the above rules.
The above described method is illustrated in FIGS. 3a and b. According to FIG. 3a, within a initial, non-sharp, image a first white pixel 300 is surrounded by five black pixels 310 and three white pixels 315. Hence, there is a majority of black pixels 315 in the initial neighborhood of the first white pixel 300. Therefore, the first white pixel 300 becomes changed to a black pixel 300'. In contrast, a second white pixel 320 is initially surrounded by four black pixels 330 and four white pixels 335 and therefore remains white. Once applying these rules on each pixel within the non-sharp image 230 of FIG. 2c, a relatively sharp image 350 may be obtained, as shown in FIG. 3b.
The method described above and other, similar prior art methods have the disadvantage of causing a general loss of information. As a result, video images of complex objects are likely to look different from the corresponding original objects. For example, small details might disappear due to the above described rules or, as another example, objects which should be in close proximity to each other might appear as a single object. In addition, the above method and certain other prior art methods are not particularly well-suited to video streaming. Hence, there is a need for a better method of improving the quality of video images for video streaming applications, such as multimedia teleconferencing.